The present invention generally relates to a system and method for improved medical imaging. Particularly, the present invention relates to a more efficient system and method for segmenting anatomical objects and correcting the segmentation of anatomical objects.
Medical diagnostic imaging systems encompass a variety of imaging modalities, such as x-ray systems, computerized tomography (CT) systems, ultrasound systems, electron beam tomography (EBT) systems, magnetic resonance (MR) systems, and the like. Medical diagnostic imaging systems generate images of an object, such as a patient, for example, through exposure to an energy source, such as x-rays passing through a patient, for example. The generated images may be used for many purposes. For instance, internal defects in an object may be detected. Additionally, changes in internal structure or alignment may be determined. Fluid flow within an object may also be represented. Furthermore, the image may show the presence or absence of objects in an object. The information gained from medical diagnostic imaging has applications in many fields, including medicine and manufacturing.
One application of utilizing the information gained from medical diagnostic imaging systems in the field of medicine is the segmentation of anatomical objects. The segmentation of anatomical objects and/or structures from two and three-dimensional images is important to allow the analysis of those anatomical objects and/or structures. For example, a particular organ or tissue may be extracted from the surrounding organs or tissues. The extracted organ or tissue may then be viewed independent of other objects that are not of interest. Such extraction allows a physician to focus only on the objects or structures of interest and develop a more accurate diagnosis and treatment strategy.
Anatomical segmentation, however, is a complex problem. Manual segmentation is a tedious, time consuming process that often yields inaccurate results. Fully automatic segmentation, although ideal, currently does not yield acceptable results. A combination of manual segmentation and automatic segmentation has yielded a number of interactive segmentation techniques.
Currently, a “live wire” technique allows a user to select a seed point on a contour, and while dragging and moving the mouse, the optimal line between the seed point and the current position may be computed. The live wire algorithm, however, may only be used in the two dimensional space and hence, this technique is a slice-by-slice segmentation, where the drawn contour on one slice becomes the initial contour on the next slice and this initial contour can be deformed.
Another strategy models edges in a surface mesh as semi-elastic linked elements in a chain. The surface mesh vertices connect the edges, so when a vertex is edited, the displacement stretches or compresses its neighboring edges. The difficulty in this strategy is to define the required extent of displacement. Another strategy that may be used is to use some medical information about the to-be-segmented object. The information may be a model, a map that can be verified to the actual medical images and then modified by the user. Since some medical objects may assume several forms, it is very hard to choose the correct model for the actual medial images or the degree of deformation allowable.
These, and other current techniques have been insufficient in the extraction of low-contrast objects. Accordingly, a system and method is needed for easier segmentation of anatomical objects. Specifically, a need exists for a segmentation technique to achieve low-contrast objects. Such a system and method may allow a user to be more efficient and effective in diagnosing and treating medical conditions.